Relations between complexity, quality and cognitive automation in mixed-model assembly

• We show relations between complexity, cognitive support and assembly errors through an industrial case.
• We show that increased Operator Choice Complexity increases assembly errors.
• Existing use of cognitive automation is low, measured on a task level.
• An increased use of cognitive automation can reduce the negative effects of Operator Choice Complexity.

Modern assembly systems are adapting to the increased mass customization resulting in shorter cycle times, more variants and increased complexity for final assembly operators. More variants require additional support functions targeted for assembly operators to avoid assembly errors. An industrial case study was carried out in order to examine the relations between complexity, quality and cognitive automation. Complexity was quantified by the measure Operator Choice Complexity (OCC). Assembly errors were measured from historical data and cognitive automation was assessed on a task level. Results show that complexity positively correlates with assembly errors and that the usage of cognitive support is low. Over 60% of all tasks in the study were performed based on own experience. Increased usage of cognitive automation is needed in final assembly to minimize the negative effects of complexity.